Results 81 to 90 of about 2,371 (202)
From Regression to Reasoning: Predicting M&A Announcement Returns With Large Language Models
European Financial Management, EarlyView.ABSTRACT This study investigates whether large language models (LLMs) can predict short‐term market reactions to M&A announcements. We prompt OpenAI's latest reasoning models (o3, GPT‐5, and GPT‐5.1) to forecast whether the combined market value of acquirer and target will increase or decrease, drawing on deal‐, firm‐, and macroeconomic data for large ...
Maximilian Schreiter +2 more
wiley +1 more source
Rational Expectations Fools' Bubbles
International Economic Review, EarlyView.ABSTRACT We develop a rational, Walrasian model of speculative bubbles inspired by the Kindleberger–Minsky view, which describes bubbles as wave‐like market processes. Touched off by an initial shock, price booms are initially self‐reinforcing but become self‐destructive later when prices surpass fundamental value.
Luis Araujo, Antonio Doblas‐Madrid
wiley +1 more source
International Transactions in Operational Research, EarlyView.Abstract We address the scheduling conflicting jobs on parallel identical machines problem with makespan minimization, a classical and computationally challenging variant of parallel machine scheduling. We develop and evaluate three distinct solution methodologies: a novel constraint programming (CP) formulation, and two metaheuristics: a multi ...
Roberto Maria Rosati +3 more
wiley +1 more source
International Journal of Aerospace Engineering, 2017 With the availability of the third civil signal in the Global Positioning System, triple-frequency Precise Point Positioning ambiguity resolution methods have drawn increasing attention due to significantly reduced convergence time.
Fei Liu, Yang Gao
doaj +1 more source
Journal of Microscopy, EarlyView.Abstract In situ synchrotron X‐ray computed tomography enables dynamic material studies. However, automated segmentation remains challenging due to complex imaging artefacts – like ring and cupping effects – and limited training data. We present a methodology for deep learning‐based segmentation by transforming high‐quality ex situ laboratory data to ...
Tristan Manchester +6 more
wiley +1 more source
Panel Sequential Group Estimation of Interactive Effects Models
Oxford Bulletin of Economics and Statistics, EarlyView.ABSTRACT This paper proposes a novel procedure to identify latent groups in the slopes of panel data models with interactive effects. The method is straightforward to apply and relies only on closed‐form estimators when evaluating the objective function.
Ignace De Vos, Joakim Westerlund
wiley +1 more source
Theoria, EarlyView.Abstract This paper argues for the significance of Kaplan's logic LD in two ways: first, by looking at how logic got along before we had LD, and second, by using it to bring out the similarity between David Hume's thesis that one cannot deduce claims about the future on the basis of premises only about the past, and the so‐called "essentiality" of the ...
Gillian Russell
wiley +1 more source
Zoologica Scripta, EarlyView.ABSTRACT Understanding insect responses to global climate change involves identifying strategies used during past climate oscillations. Phylogeography offers a powerful framework to unravel how historical climatic and geological events have shaped the spatial genetic patterns of species, providing critical insights into evolutionary processes, whereas ...
Jody H. Voges +12 more
wiley +1 more source
Utility of local capillary supply indices: Insights from computational image‐based modelling
The Journal of Physiology, EarlyView.Abstract figure legend Local capillary distribution and fibre geometry influence oxygen availability in skeletal muscle. Image‐based modelling of tissue PO2${{P}_{{{{\mathrm{O}}}_2}}}$ shows that area‐based measures of capillary supply – the local capillary density (LCDi) and local maximum diffusion distance (Dmax,i) – most accurately represent the ...
Abdullah A. Al‐Shammari +6 more
wiley +1 more source
Hunting Structural Demons in Digital Reticular Chemistry: Lessons From Metal‐Organic Frameworks
Israel Journal of Chemistry, Volume 66, Issue 4, July 2026.Digital reticular chemistry is haunted by “structural demons”, chemically invalid models lurking within massive experimental and hypothetical MOF databases. This mini‐review tracks where these anomalies enter the data pipeline, evaluate the modern computational arsenal used to detect them (from rule‐based algorithms to machine‐learning classifiers ...
Yongchul G. Chung, Myoung Soo Lah
wiley +1 more source